{"id":97535,"date":"2026-05-27T11:11:19","date_gmt":"2026-05-27T08:11:19","guid":{"rendered":"https:\/\/forklog.com\/en\/?p=97535"},"modified":"2026-05-27T11:15:11","modified_gmt":"2026-05-27T08:15:11","slug":"ibm-enhances-ai-model-with-quantum-processor","status":"publish","type":"post","link":"https:\/\/forklog.com\/en\/ibm-enhances-ai-model-with-quantum-processor\/","title":{"rendered":"IBM Enhances AI Model with Quantum Processor"},"content":{"rendered":"<p>Researchers at Multiverse Computing <a href=\"https:\/\/arxiv.org\/abs\/2605.05914\">announced<\/a> a quantum enhancement of a large language model using IBM hardware. The project involves a hybrid scheme utilizing a 156-qubit Heron processor.<\/p>\n<p>The authors described the experiment as the first &#8220;end-to-end quantum enhancement&#8221; of a <span data-descr=\"large language model\" class=\"old_tooltip\">LLM<\/span> on a superconducting processor for autoregressive text generation.<\/p>\n<p>The tests employed Meta&#8217;s Llama 3.1 8B. The base model was not further trained; its parameters were &#8220;frozen&#8221; and quantum adapters\u2014Cayley-parameterized unitary adapters (<span data-descr=\"a class of compact quantum modules that are integrated into traditional (classical) neural networks (such as large language models) for their hybrid fine-tuning\" class=\"old_tooltip\">CUA<\/span>)\u2014were added. Initially, these were trained classically, then integrated into a hybrid quantum-classical scheme.<\/p>\n<p>The experiment was conducted on the IBM Quantum System Two, an architecture for hybrid quantum systems, utilizing the 156-qubit Heron chip.<\/p>\n<p>The hybrid version reduced the perplexity of Llama 3.1 8B by 1.4%. This was achieved by adding about 6,000 parameters\u2014approximately 0.000075% of the model&#8217;s size.<\/p>\n<p>During the demonstration, the quantum-enhanced Llama correctly answered questions on astronomy and biology that the base version could not, such as whether all giant planets have rings.<\/p>\n<p>According to lead author Borja Aizpurua, the work serves as a proof of concept. The quantum blocks enabled more accurate prediction of the next token in text with minimal computational cost.<\/p>\n<p>The team aims to further reduce perplexity and increase accuracy with fewer parameters compared to fully classical approaches.<\/p>\n<p>Back in May, quantum company stocks <a href=\"https:\/\/forklog.com\/en\/news\/quantum-company-shares-surge-following-us-government-support-announcement\">rose<\/a> following the <a href=\"https:\/\/forklog.com\/en\/news\/us-invests-2-billion-in-quantum-technologies-amidst-competition-with-china\">announcement<\/a> by the U.S. Department of Commerce of a $2 billion allocation to American firms under the CHIPS R&#038;D program.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Researchers at Multiverse Computing announced a quantum enhancement of a large language model using IBM hardware.<\/p>\n","protected":false},"author":1,"featured_media":97536,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"select":"1","news_style_id":"1","cryptorium_level":"","_short_excerpt_text":"Quantum enhancement of AI model using IBM's 156-qubit processor.","creation_source":"","_metatest_mainpost_news_update":false,"footnotes":""},"categories":[3],"tags":[575,1360,167],"class_list":["post-97535","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-and-analysis","tag-quantum-computers","tag-quantum-computing","tag-research"],"aioseo_notices":[],"amp_enabled":true,"views":"20","promo_type":"1","layout_type":"1","short_excerpt":"Quantum enhancement of AI model using IBM's 156-qubit processor.","is_update":"","_links":{"self":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts\/97535","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/comments?post=97535"}],"version-history":[{"count":1,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts\/97535\/revisions"}],"predecessor-version":[{"id":97537,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts\/97535\/revisions\/97537"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/media\/97536"}],"wp:attachment":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/media?parent=97535"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/categories?post=97535"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/tags?post=97535"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}